Jig detection using scanning method base on internet of things for smart learning factory

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Ridho Hendra Yoga Perdana, Nurul Hidayati, Ahmad Wilda Yulianto, Vipkas Al Hadid Firdaus, Nila Novita Sari, Dodit Suprianto

2020 IEMTRONICS 2020 - International IOT, Electronics and Mechatronics Conference, Proceedings Conference paper Cited by 4 Quartile

Abstract

Nowadays, the evolution of a factory has pushed towards a smart learning factory. By having the ability to learn, monitor each device and the resulting product will get more precise product results according to design. Detection of a place to put a product or called a jig on a shuttle whose number is different becomes something that is often missed from observation. With the scanning method with five pieces of ultrasonic sensors, the detection speed is 50 μs, and the detection accuracy is 100% for distances less than 25cm. The detection process of the jig is sent and stored by IoT Gateway as a Big Data Cluster via wifi media with a performance of 99.4%. The process of storing data on the IoT Cloud as the Main Big Data has a performance of 100% of the data on the IoT Gateway. © 2020 IEEE.

Affiliations

State Polytechnic of Malang, Department of Electrical Engineering, Malang, Indonesia; State Polytechnic of Malang, Department of Information Technology, Malang, Indonesia; Politeknik Negeri Bandung, Department of Electrical Engineering, Bandung, Indonesia